A Multistate Frequency Reconfigurable Monopole Antenna Using Fluidic Channels
Bibliographic record
Abstract
A reconfigurable microstrip monopole antenna that uses three closely spaced substrate milled channels filled with either air or dielectric fluid is presented. Based on the number of channels filled with fluid, four states-namely states 0, 1, 2, and 3-of operation are selected. Introduction of fluid (distilled water) in the channel modifies the effective permittivity of the dielectric medium and perturbs the E-field distribution in vicinity to the antenna arm. The position and size of channels are optimized to maximize the shift in operating frequency and $S_{11}<; $$-$10 dB impedance bandwidth through full-wave electromagnetic (HFSS) simulations. A prototype of the antenna is fabricated and measured, exhibiting frequency shifts of 12.0%, 17.9%, and 23.7% with impedance bandwidth of 32.0%, 30.1%, and 29.9% in states 1, 2, and 3 of the antenna, respectively. The reference state, i.e., state 0, offers 34.7% impedance bandwidth. The measured peak gains achieved are 2.4, 1.6, 1.2, and 0.3 dBi for states 0, 1, 2, and 3, respectively. In all the states of operation, the radiation pattern remains stable and omnidirectional.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".